درخت حوزه‌های تخصصی

Environment quality and its determinants are one of the main challenges of the present and future of humanity and sustainable development is interpreted in the direction of preserving and improving the environment. In recent years, many studies have been conducted on the factors affecting environmental quality. One of the main topics that have been less considered in the related studies is the impact of governance on the quality of the environment. In this study, the impact of good governance components, including economic freedom, trade freedom, and political freedom, on the Environmental Performance Index (EPI) and its sub-indices including environmental health, ecosystem vitality, and climate change is investigated. The data required for statistical analysis are related to Middle East and North Africa region countries and Turkiye (MENAT) during 2000-2021. The panel data method was used to estimate the model and examine the relationship between the variables. The findings show that there is a positive and significant relationship between economic freedom and political freedom with the environmental performance index (EPI), and there is no significant relationship between trade freedom and EPI. </span>In addition, the study found that economic freedom had a detrimental effect on ecosystem vitality and climate change, leading to negative impacts in these areas. However, it had a positive impact on environmental health, indicating that it contributed positively to this aspect. On the other hand, political freedom was observed to have a positive effect on the vitality of the ecosystem and climate change. However, it did not have a significant impact on the overall health of the environment, suggesting that its influence was more prominent in specific areas related to ecosystem vitality and climate change. <span style="layout-grid-mode: line;" data-mce-fragment="1">The result of this research showed that economic freedom has led to more investment in the oil and gas sector of MENA countries, and therefore wastewater and gas emissions have had a negative impact on the vitality of the environment and climate change, but with the increase in production and sales of oil and Gas, per capita income of countries has increased, and environmental health has improved. Also, considering that political freedom among the MENA region has a lot of diversity, the results showed that the countries with more political freedom, through greater awareness of the society and more accountability of the governments and the establishment of environmental protection laws, had a positive impact on the environment. Of course, the environmental health index is more influenced by the economic situation and per capita production of countries and political freedom has little effect on it.

Volatility and risk measurement are essential parameters in risk management programs that can affect economic activities and public confidence in the stock market. Also, these two are the keys in the studies that connect the stock market, economic growth, and other financial factors. In recent years, due to the instability in the Tehran Stock Exchange, controlling the adverse effects caused by the volatility of stock prices, predicting and modeling price dynamics, and measuring risk have become necessary for the participants in this market. In the present research, the class of hidden Markovian index models of conditional variance Heteroskedasticity (HM-GARCH) is used to predict the volatility of stock prices and accounts of the Tehran Stock Exchange. For a comprehensive review, the models are selected to include the characteristics of volatility clustering, asymmetry in volatility (leverage effect), and heavy tail of stock returns (with t-student distribution). Based on RMSE and AME criteria, the HM-EGARCH-Normal Exponential GARCH model with normal distribution is more effective than other models in predicting stock market volatility. Therefore, leverage is necessary to analyze stock market risks using hidden Markov models, but heavy tail distribution is unnecessary. The results indicate that the HM-EGARCH-Normal model appropriately assesses volatility and improves market transparency and risk management forecasts. Also, the VaR and CVaR market risk assessment post-tests using Kupiec and DQ tests do not show evidence of overestimation or underestimation.